PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment

<p>Abstract</p> <p>Background</p> <p>The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.</p> <p>Results</p> <p><monospace>PhyloSim</monospace> is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, <monospace>PhyloSim</monospace> can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing <monospace>PhyloSim</monospace> to be adapted to specific needs.</p> <p>Conclusions</p> <p>Close integration with <monospace>R</monospace> and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that <monospace>PhyloSim</monospace> will be useful to future studies involving simulated alignments.</p

SUMO chain formation is required for response to replication arrest in S. pombe

SUMO is a ubiquitin-like protein that is post-translationally attached to one or more lysine residues on target proteins. Despite having only 18% sequence identity with ubiquitin, SUMO contains the conserved betabetaalphabetabetaalphabeta fold present in ubiquitin. However, SUMO differs from ubiquitin in having an extended N-terminus. In S. pombe the N-terminus of SUMO/Pmt3 is significantly longer than those of SUMO in S. cerevisiae, human and Drosophila. Here we investigate the role of this N-terminal region. We have used two dimensional gel electrophoresis to demonstrate that S. pombe SUMO/Pmt3 is phosphorylated, and that this occurs on serine residues at the extreme N-terminus of the protein. Mutation of these residues (in pmt3-1) results in a dramatic reduction in both the levels of high Mr SUMO-containing species and of total SUMO/Pmt3, indicating that phosphorylation of SUMO/Pmt3 is required for its stability. Despite the significant reduction in high Mr SUMO-containing species, pmt3-1 cells do not display an aberrant cell morphology or sensitivity to genotoxins or stress. Additionally, we demonstrate that two lysine residues in the N-terminus of S. pombe SUMO/Pmt3 (K14 and K30) can act as acceptor sites for SUMO chain formation in vitro. Inability to form SUMO chains results in aberrant cell and nuclear morphologies, including stretched and fragmented chromatin. SUMO chain mutants are sensitive to the DNA synthesis inhibitor, hydroxyurea (HU), but not to other genotoxins, such as UV, MMS or CPT. This implies a role for SUMO chains in the response to replication arrest in S. pomb

Brain structural changes and neuropsychological impairments in male polydipsic schizophrenia

BACKGROUND: Polydipsia frequently occurs in schizophrenia patients. The excessive water loading in polydipsia occasionally induces a hyponatremic state and leads to water intoxication. Whether polydipsia in schizophrenic patients correlates with neuropsychological impairments or structural brain changes is not clear and remains controversial. METHODS: Eight polydipsic schizophrenia patients, eight nonpolydipsic schizophrenia patients, and eight healthy controls were recruited. All subjects underwent magnetic resonance imaging (MRI) and neuropsychological testing. Structural abnormalities were analyzed using a voxel-based morphometry (VBM) approach, and patients’ neuropsychological function was assessed using the Brief Assessment of Cognition in Schizophrenia, Japanese version (BACS-J). RESULTS: No significant differences were found between the two patient groups with respect to the clinical characteristics. Compared with healthy controls, polydipsic patients showed widespread brain volume reduction and neuropsychological impairment. Furthermore, the left insula was significantly reduced in polydipsic patients compared with nonpolydipsic patients. These nonpolydipsic patients performed intermediate to the other two groups in the neuropsychological function test. CONCLUSIONS: It is possible that polydipsia or the secondary hyponatremia might induce left insula volume reduction. Furthermore, this structural brain change may indirectly induce more severe neuropsychological impairments in polydipsic patients. Thus, we suggest that insula abnormalities might contribute to the pathophysiology of polydipsic patients

An Age-Structured Extension to the Vectorial Capacity Model

Vectorial capacity and the basic reproductive number (R(0)) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention.Based on survival analysis we derived new equations for vectorial capacity and R(0) that are valid for any pattern of age-dependent (or age-independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies.Accounting for age-dependent vector mortality in estimates of vectorial capacity and R(0) was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R(0) is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R(0) ∼ 1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field

Non-Negative Matrix Factorization for Learning Alignment-Specific Models of Protein Evolution

Models of protein evolution currently come in two flavors: generalist and specialist. Generalist models (e.g. PAM, JTT, WAG) adopt a one-size-fits-all approach, where a single model is estimated from a number of different protein alignments. Specialist models (e.g. mtREV, rtREV, HIVbetween) can be estimated when a large quantity of data are available for a single organism or gene, and are intended for use on that organism or gene only. Unsurprisingly, specialist models outperform generalist models, but in most instances there simply are not enough data available to estimate them. We propose a method for estimating alignment-specific models of protein evolution in which the complexity of the model is adapted to suit the richness of the data. Our method uses non-negative matrix factorization (NNMF) to learn a set of basis matrices from a general dataset containing a large number of alignments of different proteins, thus capturing the dimensions of important variation. It then learns a set of weights that are specific to the organism or gene of interest and for which only a smaller dataset is available. Thus the alignment-specific model is obtained as a weighted sum of the basis matrices. Having been constrained to vary along only as many dimensions as the data justify, the model has far fewer parameters than would be required to estimate a specialist model. We show that our NNMF procedure produces models that outperform existing methods on all but one of 50 test alignments. The basis matrices we obtain confirm the expectation that amino acid properties tend to be conserved, and allow us to quantify, on specific alignments, how the strength of conservation varies across different properties. We also apply our new models to phylogeny inference and show that the resulting phylogenies are different from, and have improved likelihood over, those inferred under standard models

A Screen for Spore Wall Permeability Mutants Identifies a Secreted Protease Required for Proper Spore Wall Assembly

The ascospores of Saccharomyces cerevisiae are surrounded by a complex wall that protects the spores from environmental stresses. The outermost layer of the spore wall is composed of a polymer that contains the cross-linked amino acid dityrosine. This dityrosine layer is important for stress resistance of the spore. This work reports that the dityrosine layer acts as a barrier blocking the diffusion of soluble proteins out of the spore wall into the cytoplasm of the ascus. Diffusion of a fluorescent protein out of the spore wall was used as an assay to screen for mutants affecting spore wall permeability. One of the genes identified in this screen, OSW3 (RRT12/YCR045c), encodes a subtilisin-family protease localized to the spore wall. Mutation of the active site serine of Osw3 results in spores with permeable walls, indicating that the catalytic activity of Osw3 is necessary for proper construction of the dityrosine layer. These results indicate that dityrosine promotes stress resistance by acting as a protective shell around the spore. OSW3 and other OSW genes identified in this screen are strong candidates to encode enzymes involved in assembly of this protective dityrosine coat

Addressing Inter-Gene Heterogeneity in Maximum Likelihood Phylogenomic Analysis: Yeasts Revisited

Phylogenomic approaches to the resolution of inter-species relationships have become well established in recent years. Often these involve concatenation of many orthologous genes found in the respective genomes followed by analysis using standard phylogenetic models. Genome-scale data promise increased resolution by minimising sampling error, yet are associated with well-known but often inappropriately addressed caveats arising through data heterogeneity and model violation. These can lead to the reconstruction of highly-supported but incorrect topologies. With the aim of obtaining a species tree for 18 species within the ascomycetous yeasts, we have investigated the use of appropriate evolutionary models to address inter-gene heterogeneities and the scalability and validity of supermatrix analysis as the phylogenetic problem becomes more difficult and the number of genes analysed approaches truly phylogenomic dimensions. We have extended a widely-known early phylogenomic study of yeasts by adding additional species to increase diversity and augmenting the number of genes under analysis. We have investigated sophisticated maximum likelihood analyses, considering not only a concatenated version of the data but also partitioned models where each gene constitutes a partition and parameters are free to vary between the different partitions (thereby accounting for variation in the evolutionary processes at different loci). We find considerable increases in likelihood using these complex models, arguing for the need for appropriate models when analyzing phylogenomic data. Using these methods, we were able to reconstruct a well-supported tree for 18 ascomycetous yeasts spanning about 250 million years of evolution

Cellular Radiosensitivity: How much better do we understand it?

Purpose: Ionizing radiation exposure gives rise to a variety of lesions in DNA that result in genetic instability and potentially tumorigenesis or cell death. Radiation extends its effects on DNA by direct interaction or by radiolysis of H2O that generates free radicals or aqueous electrons capable of interacting with and causing indirect damage to DNA. While the various lesions arising in DNA after radiation exposure can contribute to the mutagenising effects of this agent, the potentially most damaging lesion is the DNA double strand break (DSB) that contributes to genome instability and/or cell death. Thus in many cases failure to recognise and/or repair this lesion determines the radiosensitivity status of the cell. DNA repair mechanisms including homologous recombination (HR) and non-homologous end-joining (NHEJ) have evolved to protect cells against DNA DSB. Mutations in proteins that constitute these repair pathways are characterised by radiosensitivity and genome instability. Defects in a number of these proteins also give rise to genetic disorders that feature not only genetic instability but also immunodeficiency, cancer predisposition, neurodegeneration and other pathologies. Conclusions: In the past fifty years our understanding of the cellular response to radiation damage has advanced enormously with insight being gained from a wide range of approaches extending from more basic early studies to the sophisticated approaches used today. In this review we discuss our current understanding of the impact of radiation on the cell and the organism gained from the array of past and present studies and attempt to provide an explanation for what it is that determines the response to radiation

Simultaneous genotyping of multiple polymorphisms in human serotonin transporter gene and detection of novel allelic variants

The serotonin transporter, called SLC6A4, SERT or 5-HTT, modulates neurotransmission by removal of serotonin from the synapse of serotonergic neurons, facilitating serotonin reuptake into the presynaptic terminus. Selective serotonin reuptake inhibitors block the action of the serotonin transporter and are used to treat depression and other neuropsychiatric disorders. Three polymorphisms in the 5-HTT gene have been implicated in treatment response and neuropsychiatric disorders. A 44-bp promoter ins/del polymorphism (5-HTTLPR) produces primarily long and/or short alleles due to either 14 (short) or 16 (long) repeats of variably conserved 20–23 bp units. Also implicated, a 17–18 bp variable number tandem repeat found in intron2 (StIn2) is expressed as triallelic content with 9, 10, or 12 repeats (StIn2.9, StIn2.10 or StIn2.12). Finally, a single nucleotide polymorphism rs25531 located within the promoter polymorphic-linked region alters the function of the long promoter allele. We developed a PCR-based fragment analysis assay, which is analyzed on an ABI sequencer, whereby we are able to detect all three genotypes simultaneously. Using this technique, we identified novel sequences, which demonstrate promoter repeat regions containing (1) a 17 repeat with rs25531 A/G polymorphism, (2) two with 18-repeat units, (3) one with 20-repeat units and (4) a 24-repeat sequence. The novel repeats were confirmed by direct sequencing of gel-purified amplicons